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Network Simulation and Testing. Polly Huang EE NTU http://cc.ee.ntu.edu.tw/~phuang phuang@cc.ee.ntu.edu.tw. Today. General System Analysis The Internet Evaluating the Internet. The Engineering Cycle. For a running system Monitor the usage Characterize the workload
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Network Simulation and Testing Polly Huang EE NTU http://cc.ee.ntu.edu.tw/~phuang phuang@cc.ee.ntu.edu.tw
Today General System Analysis The Internet Evaluating the Internet
The Engineering Cycle • For a running system • Monitor the usage • Characterize the workload • Predict for the future • Revise original design • Instrument the changes • And back to the top Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
Chicken or Egg • But where did it all start? • It depends • The Internet case? • The alternatives selection • But it’s really just experts’ intuition Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
Sounds Easy… Yah, easy to talk about it… All Sorts of Problems in Practice…
Monitoring the Usage • Monitor the usage • Measurement methodology • Measurement tools • Characterize the workload • Predict for the future • Revise original design • Instrument the changes Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
Characterizing the Workload • Monitor the usage • Characterize the workload • Modeling the measured data • The model needs to remain valid for data from taken at different time/location • Predict for the future • Revise original design • Instrument the changes Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
Predicting the Performance • Monitor the usage • Characterize the workload • Predict for the future • Anticipate the user access pattern, demand increase • Evaluate the existing’s capacity • Revise original design • Instrument the changes Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
Designing the Alternatives • Monitor the usage • Characterize the workload • Predict for the future • Revise original design • If the current system won’t live up to the challenge, how can it be changed… • Effective solutions • Instrument the changes Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
Instrumenting the Changes • Monitor the usage • Characterize the workload • Predict for the future • Revise original design • Instrument the changes • Politics Workload Characterization Performance Prediction Usage Monitoring General System Alternatives Selection System Instrumentation
If This is the Telephone Network • Monitor the usage • The big players place monitors all over the places in their own networks to collect data • Characterize the workload • Fit the collected data to the well-known models • Human voice is Poisson • For some reason, the nature works this way.
Telephone Network (cont) • Predict for the future • Queuing theory: • Safe to supply 1bandwidth for a call of average rate 1 • 1 +2 bandwidth for calls of average rate 1 and 2 • Linear programming: • Given the max tolerable blocking rate, max the profit • Revise original design • Mostly infrastructure-ral • I.e., rearranging or adding switches&cables • Instrument the changes • Have full authority to change
No Real Difficulties Quite a Profitable Business
Is the data network as profitable? Let’s review the data network.
Today General System Analysis The Internet Evaluating the Internet
Internet: Basic Components • Think the postal system • Nodes • End hosts and less number of routers • Homes and local/remote post offices • Links • Connecting nodes (Access net, Ethernet, T1, T3, OC3, OC12, etc) • Roads/streets between homes and post offices
Internet: Basic Constructions • Packets • Destined to IP addresses (129.132.66.28) • Destined to postal addresses (1, Sec. 4 Roosevelt Rd.) • Protocols • Packets sent with TCP (reliable) • Packets sent with registered mail with confirmation • But no congestion control • Other protocols…
Application: supporting network applications FTP, SMTP, HTTP Transport: host-host data transfer TCP, UDP Network: routing of datagrams from source to destination IP (addressing, routing, forwarding) Link: data transfer between neighboring network elements Error Checking, MAC, Ethernet Physical: bits “on the wire” application transport network link physical Internet Protocol Stack
P2P • Distributed directory for effective searching • Mobile and Wireless • Isolating drops due to bit error for TCP • Routing for dynamic networks • Handling the hidden terminal problem • QoS • Problem Detection (loss, congestion) • Control (end-to-end, router-assisted) Data Network Research(Side-Bar) • Application • HTTP evolution • Web caching • Transport • TCP evolution • Network • Unicast routing • Multicast routing
Application: supporting network applications FTP, SMTP, HTTP Transport: host-host data transfer TCP, UDP Network: routing of datagrams from source to destination IP (addressing, routing, forwarding) Link: data transfer between neighboring network elements Error Checking, MAC, Ethernet Physical: bits “on the wire” application transport network link physical Internet Protocol Stack(Back to the Topic)
network link physical application transport network link physical application transport network link physical application transport network link physical application transport network link physical data data Physical communication
Mesh of interconnected routers Routers under the same administration are deemed within one Autonomous System (or domain) Backbone ASs vs. edge ASs Data sent thru net in discrete “chunks” Packet switching As opposed to circuit switching The Network Core
Internet: The Network • The Global Internet consists of Autonomous Systems (AS) interconnected with each other: • Stub AS: small corporation: one connection to other AS’s • Multihomed AS: large corporation (no transit): multiple connections to other AS’s • Transit AS: provider, hooking many AS’s together • Two-level routing: • Intra-AS: administrator responsible for choice of routing algorithm within network • Inter-AS: unique standard for inter-AS routing: BGP
Internet AS Hierarchy Inter-AS border (exterior gateway) routers Intra-ASinterior (gateway) routers
Circuit-Switched NetworkThe Telephone Network Fixed size pipe from her to him
Internet: The Traffic • Differences: • packets as low-level component • multiple kinds of traffic • packets from different sources of different nature all mixed up
Let’s come back to this question: Is the data network as profitable?
Today General System Analysis The Internet Evaluating the Internet
What If This is the Internet • Monitor the usage • The big players place monitors all over the places in their own networks to collect data • Would this give you representative data? • Characterize the workload • Fit the collected data to the well-known models • Human voice is Poisson • Are Web browsing, Email, P2P, etc traffic Poisson?
Internet (cont) • Predict for the future • Queuing theory: • Save to supply 1bandwidth for a call of average rate 1 • 1 +2 bandwidth for calls of average rate 1 and 2 • Average, a good measure? Does traffic add up? • Revise original design • Mostly infrastructure-ral • Still infrastructure-ral? • Instrument the changes • Have full authority to change • Can the big players dictate?
For the Most of These Questions The Answer is NO
Repeat The Engineering Cycle • For the Internet • Monitor the usage • Passive and active measurement • Characterize the workload • Traffic, topology, routing errors, access pattern modeling • Predict for the future • Scalable simulation & testing tools • Revise original design • Protocol and Infrastructure • Instrument the changes • IETF Internet Characterization Scalable Packet-level Simulation Reliable Measurement The Internet Structure & Design Decision Internet Instrumentation (IETF)
Relevance to This Course • Objective • We know something better than others do • We do the right experiments so the results will be convincing • Requirements • Representative (or best known) workload • Trusted (most used) tools
Workload • Traffic • Packet-level characteristics • Correlation to protocol and user behavior • Know better how to generate traffic for your experiments • Topology • Router/domain-level connectivity • Correlation to routing • Know better how to generate topology for your experiments
Tools • ns-2 • About the most popular in the research community • Platform for cross-examination • dummynet • Not the only one • But an easy and thus often-used one
The Useful Theory Statistics Evaluation Methodology
Keyword: Heavy-tailed • It turned out computer processes tend to be heavy-tailed or power-law distributed! • CPU time consumed by Unix processes • Size of Unix files • Size of compressed video frames • Size of FTP bursts • Telnet packet interarrivals • Size of Web items • Ethernet bursts
Review Some Statistics • Density vs. Distribution • Poisson • Exponential • Pareto • Self-similarity
Density vs. Distribution • Density is the probability of certain events to happen • f(x) • Distribution is usually referred to as the accumulative density • f(0)+f(dz)+f(2*dz)+…+f(x) • F(x) = 0->xf(z) dz
Exponential • # of time units between events • f(x) = ce-cx
Poisson • # of events per time unit • f(x) = ce-c/x!
Pareto • One of the heavy-tailed distributions • f(x) = c*kc/(xc+1)
Distinguishing Them • Density • Log density • Log-log density
Density Log Density Log-Log Density
Exp Exponential Heavy tailed Teletraffic vs. Data traffic • Teletraffic • Data traffic Exponential
Measured Internet Traffic Poisson Process 100s • Performance problem every • 1-2 hour (network lags!) • Profitable business? 10s 1s • High variability (bursty) • Long-range dependence • Self-similarity 100ms 10ms